QED-Nano (Quantized)
Description
This model is a 4-bit quantized version of the original lm-provers/QED-Nano model, optimized for reduced memory usage while maintaining performance.
Quantization Details
- Quantization Type: 4-bit
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
- bnb_4bit_quant_storage: uint8
- Original Footprint: 8044.94 MB (BFLOAT16)
- Quantized Footprint: 2594.96 MB (UINT8)
- Memory Reduction: 67.7%
Usage
from transformers import AutoModel, AutoTokenizer
model_name = "QED-Nano-bnb-4bit-nf4"
model = AutoModel.from_pretrained(
"manu02/QED-Nano-bnb-4bit-nf4",
)
tokenizer = AutoTokenizer.from_pretrained("manu02/QED-Nano-bnb-4bit-nf4", use_fast=True)
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Model tree for manu02/QED-Nano-bnb-4bit-nf4-dq
Base model
Qwen/Qwen3-4B-Thinking-2507
Finetuned
lm-provers/QED-Nano-SFT
Finetuned
lm-provers/QED-Nano